WO2024053800A1 - Procédé et dispositif de surveillance de traitement au laser - Google Patents

Procédé et dispositif de surveillance de traitement au laser Download PDF

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Publication number
WO2024053800A1
WO2024053800A1 PCT/KR2022/021512 KR2022021512W WO2024053800A1 WO 2024053800 A1 WO2024053800 A1 WO 2024053800A1 KR 2022021512 W KR2022021512 W KR 2022021512W WO 2024053800 A1 WO2024053800 A1 WO 2024053800A1
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WO
WIPO (PCT)
Prior art keywords
laser
target
pattern
laser processing
control unit
Prior art date
Application number
PCT/KR2022/021512
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English (en)
Korean (ko)
Inventor
이용관
김수경
Original Assignee
한국공학대학교산학협력단
주식회사 리쉐니에
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Publication of WO2024053800A1 publication Critical patent/WO2024053800A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
    • B23K26/00—Working by laser beam, e.g. welding, cutting or boring
    • B23K26/02—Positioning or observing the workpiece, e.g. with respect to the point of impact; Aligning, aiming or focusing the laser beam
    • B23K26/03—Observing, e.g. monitoring, the workpiece
    • B23K26/032—Observing, e.g. monitoring, the workpiece using optical means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
    • B23K26/00—Working by laser beam, e.g. welding, cutting or boring
    • B23K26/02—Positioning or observing the workpiece, e.g. with respect to the point of impact; Aligning, aiming or focusing the laser beam
    • B23K26/03—Observing, e.g. monitoring, the workpiece
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
    • B23K26/00—Working by laser beam, e.g. welding, cutting or boring
    • B23K26/36—Removing material
    • B23K26/38—Removing material by boring or cutting
    • B23K26/382—Removing material by boring or cutting by boring
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
    • B23K31/00—Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by only one of the preceding main groups
    • B23K31/12—Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by only one of the preceding main groups relating to investigating the properties, e.g. the weldability, of materials
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
    • B23K31/00—Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by only one of the preceding main groups
    • B23K31/12—Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by only one of the preceding main groups relating to investigating the properties, e.g. the weldability, of materials
    • B23K31/125—Weld quality monitoring

Definitions

  • the present invention relates to a laser processing monitoring method and device.
  • the present invention was derived from research conducted as part of the National Research Foundation of Korea's ICT and Broadcasting Innovation Talent Training Project below.
  • laser devices are often used to change the material of the substrate surface, machining via holes, or forming specific patterns.
  • technology is used to process the laser beam into a special shape, to shape the spatial shape of the laser into lines, surfaces, etc., that is, to maintain the spatial intensity of the beam in a specific shape or to minimize the transition width at the edge.
  • Technology is being developed.
  • the characteristics of such a precisely formed laser beam may be modified by environmental factors, unlike the initial recipe settings, before being irradiated to the imaging surface, i.e., the target, causing abnormalities in the processed product.
  • the imaging surface i.e., the target
  • processing quality inspection is usually conducted after the process is completed, so it is difficult to correct or rework defective molds, resulting in high mold disposal costs.
  • Embodiments of the present invention to solve these conventional problems provide a laser processing monitoring method and device that can check processing defects in real time depending on the type of target during target processing.
  • embodiments of the present invention provide a laser processing monitoring method and device that can omit a separate defect inspection process for defect inspection by checking processing defects in real time when processing a target.
  • the laser processing monitoring method includes the steps of irradiating a laser to the target according to a processing start signal of the target, receiving reflected light from which the laser is reflected by the target, and a reflection amount pattern for the reflected light. It is characterized in that it includes the step of checking and detecting whether the hole generated by the laser irradiation is defective based on the reflection amount pattern.
  • the step of detecting whether the hole is defective includes comparing a pre-stored learning pattern with the confirmed reflection amount pattern, and confirming that the hole is defective when the learning pattern and the reflection amount pattern differ by more than a threshold value. It is characterized by:
  • the method further includes the step of storing the learning pattern in consideration of the type of the target.
  • the method further includes the step of storing the learning pattern in consideration of the spacing of the holes and the diameter of the holes.
  • the step of storing the learning pattern is characterized in that it is a step of storing the learning pattern generated using an unsupervised autoencoder.
  • the laser processing monitoring device controls the processing unit and the processing unit including a light source unit for irradiating a laser to a target and a light receiving unit for receiving reflected light reflected by the laser, and irradiates the laser at the light receiving unit. It is characterized by including a control unit that checks the reflection amount pattern for the received reflected light and detects whether the hole generated by the laser irradiation is defective based on the reflection amount pattern.
  • control unit compares the previously stored learning pattern with the confirmed reflection amount pattern and determines that a defect has occurred in the hole if the difference is more than a threshold value.
  • control unit stores the learning pattern in the memory in consideration of the type of the target.
  • control unit stores the learning pattern in the memory in consideration of the spacing of the holes and the diameter of the holes.
  • control unit is characterized in that it generates the learning pattern using an unsupervised autoencoder.
  • the laser processing monitoring method and device checks processing defects in real time according to the type of target when processing a target, thereby omitting a separate defect inspection process, thereby determining the types and characteristics of defects according to the type of target. can be checked and has the effect of minimizing the time spent on the defect inspection process.
  • FIG. 1 is a diagram showing an electronic device for monitoring laser processing according to an embodiment of the present invention.
  • Figure 2 is a flowchart for explaining a method of performing laser processing monitoring according to an embodiment of the present invention.
  • FIG. 1 is a diagram showing an electronic device for monitoring laser processing according to an embodiment of the present invention.
  • the electronic device 100 may include a communication unit 110, a processing unit 120, an input unit 130, a display unit 140, a memory 150, and a control unit 160.
  • the processing unit 120 may include a light source unit 121 and a light receiving unit 122.
  • the communication unit 110 may receive learning patterns (hereinafter referred to as learning data) from an external server through communication with an external server (not shown). To this end, the communication unit 110 performs wireless communication such as 5G ( 5th generation communication), LTE-A (Long Term Evolution-Advanced), LTE (Long Term Evolution), and Wi-Fi (Wireless Fidelity) with an external server. can do.
  • 5G 5th generation communication
  • LTE-A Long Term Evolution-Advanced
  • LTE Long Term Evolution
  • Wi-Fi Wireless Fidelity
  • the learning data is learning data to which processing conditions and learning patterns are mapped, and can be generated using an AI algorithm stored on an external server.
  • Processing conditions are conditions for the type of target (e.g., metal, ceramic, etc.), target thickness, via hole spacing, via hole diameter, and number of via holes, and the learning pattern is the reflection amount pattern when the target is processed normally according to the processing conditions. This may be a learned and generated pattern.
  • the external server can apply the normal reflection amount pattern obtained from the electronic device 100 at the time the target is normally processed as input to the AI algorithm.
  • the external server trains in an unsupervised manner by applying the processing conditions and reflection pattern for the environment set during target processing, such as target type, target thickness, via hole spacing, via hole diameter, and number of via holes, as input to the AI algorithm. You can create an autoencoder model, which is an artificial neural network, and use it to generate learning data to which processing conditions and learning patterns are mapped.
  • the processing unit 120 may include a light source unit 121 for irradiating laser light (hereinafter collectively referred to as laser) and a light receiving unit 122 for receiving reflected light.
  • the laser irradiated from the light source unit 121 is reflected by the target to generate reflected light, and the light receiving unit 122 receives the reflected light generated by being reflected by the target.
  • the light source unit 121 may be formed with a plurality of light sources to irradiate according to the number of via holes included in the processing conditions.
  • the light receiving unit 122 generates light receiving data using the received reflected light and provides this to the control unit 160.
  • the light receiving unit 122 may mean a photo diode sensor, etc.
  • the input unit 130 generates input data in response to input from an operator operating the electronic device 100.
  • the input unit 130 may include at least one input means among a key pad, dome switch, touch panel, touch key, and button.
  • the display unit 140 outputs output data according to the operation of the electronic device 100.
  • the display unit 140 includes a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, and a micro electro mechanical system (MEMS). systems) displays and electronic paper displays.
  • the display unit 140 may be combined with the input unit 130 and implemented as a touch screen.
  • the memory 150 stores operation programs of the electronic device 100.
  • the memory 150 may store an algorithm for generating a reflection amount pattern based on the light-receiving data generated by the light receiving unit 122 and an algorithm for generating learning data using the reflection amount pattern.
  • the memory 150 may store learning data mapped to a learning pattern when the target is normally processed according to processing conditions such as target type, target thickness, via hole spacing, via hole diameter, and number of via holes.
  • the learning pattern refers to a pattern in which the reflection amount pattern when the target is normally processed according to processing conditions is learned.
  • the control unit 160 can generate learning data through testing and store it in the memory 150, and can store learning data received from an external server in the memory 150 through communication with an external server.
  • the control unit 160 can call the AI algorithm stored in the memory 150 and apply the normal reflectance pattern obtained when the target is normally processed as an input to the AI algorithm.
  • the control unit 160 applies processing conditions for the environment set during target processing, that is, target type, target thickness, via hole spacing, via hole diameter, and number of via holes, etc., as input to the AI algorithm, You can create an autoencoder model, which is an artificial neural network.
  • the control unit 160 controls the processing unit 120 to irradiate the laser to the target.
  • the control unit 160 checks the reflection amount pattern using the light reception data generated by the light receiving unit 122, which receives the reflected light reflected by the laser target.
  • the control unit 160 can detect defects generated during processing of a target caused by laser irradiation based on the confirmed reflection amount pattern.
  • the control unit 160 controls the light source unit 121 according to the processing start signal to irradiate the laser to the target.
  • the processing start signal may include processing conditions for the type of target to be processed, the thickness of the target, via hole spacing, via hole diameter, and number of via holes.
  • the laser irradiated from the light source unit 121 is reflected by the target to generate reflected light.
  • the generated reflected light is received by the light receiving unit 122, and the light receiving unit 122 generates light receiving data based on the reflected light.
  • the light receiving unit 122 provides the confirmed light receiving data to the control unit 160.
  • the control unit 160 uses the received light data to check the reflection amount pattern for the reflected light.
  • the reflected light may be the largest, and when processing of via holes, etc. on the target is completed, the reflected light may be smallest. In other words, the size of the reflected light may gradually decrease over time while the laser is irradiated to the target.
  • the control unit 160 can check the reflection amount pattern of the reflected light generated over time when the laser is irradiated to the target.
  • the control unit 160 calls learning data previously stored in the memory 150.
  • the control unit 160 compares the confirmed reflection amount pattern with the learning pattern included in the called learning data.
  • the control unit 160 checks the learning pattern mapped to the same processing conditions as the processing conditions included in the processing start signal among the learning data. At this time, the control unit 160 may compare the confirmed reflection amount pattern and the called learning pattern. If the difference between the two reflection amount patterns is greater than or equal to a threshold, the control unit 160 may determine that a defect has been detected during target processing and display this on the display unit 140.
  • Figure 2 is a flowchart for explaining a method of performing laser processing monitoring according to an embodiment of the present invention.
  • step 201 the control unit 160 performs step 203 when a processing start signal for processing the target with a laser is received from the input unit 130. If the processing start signal is not received, the control unit 160 performs step 203. wait for At this time, the processing start signal may include processing conditions for the type of target to be processed, the thickness of the target, via hole spacing, via hole diameter, and number of via holes.
  • step 203 the control unit 160 controls the light source unit 121 according to the received processing start signal to irradiate the laser to the target.
  • step 205 the control unit 160 receives and confirms the light reception data generated by the light reception unit 122. More specifically, the laser irradiated to the target is reflected on the target to generate reflected light, and the light receiving unit 122 generates light receiving data based on the received reflected light and provides it to the control unit 160.
  • step 207 the control unit 160 checks the reflection amount pattern for the reflected light using the received light data.
  • the reflected light may be the largest, and when processing of via holes, etc. on the target is completed, the reflected light may be smallest. In other words, the size of the reflected light may gradually decrease over time as the laser is irradiated to the target.
  • the control unit 160 can check the reflection amount pattern of the reflected light generated over time when the laser is irradiated to the target.
  • step 209 the control unit 160 calls the learning data previously stored in the memory 150. At this time, the control unit 160 can call learning data having the same processing conditions as the type of target to be processed, the thickness of the target, via hole spacing, via hole diameter, and number of via holes included in the processing start signal received in step 201. there is.
  • step 211 the control unit 160 compares the reflection pattern identified in step 207 with the learning pattern included in the learning data called in step 209.
  • step 211 if the difference between the reflection amount pattern confirmed in step 207 and the called learning pattern is greater than or equal to a threshold, the control unit 160 performs step 213, and if the difference is less than the threshold, the process can be terminated.
  • the control unit 160 may determine that a defect has been detected during processing the target and display this on the display unit 140.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Optics & Photonics (AREA)
  • Mechanical Engineering (AREA)
  • Plasma & Fusion (AREA)
  • Quality & Reliability (AREA)
  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
  • Laser Beam Processing (AREA)

Abstract

La présente invention se rapporte à un procédé et à un dispositif de surveillance de traitement au laser, le procédé comprenant les étapes consistant : à faire rayonner un laser vers une cible en fonction d'un signal pour démarrer le traitement de la cible; à recevoir une lumière réfléchie qui est le laser réfléchi à partir de la cible; à identifier un motif de quantité de réflexion de la lumière réfléchie; et à détecter si oui ou non un trou généré par le rayonnement laser est défectueux sur la base du motif de quantité de réflexion. En outre, la présente invention peut présenter d'autres modes de réalisation.
PCT/KR2022/021512 2022-09-08 2022-12-28 Procédé et dispositif de surveillance de traitement au laser WO2024053800A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR10-2022-0114081 2022-09-08
KR1020220114081A KR20240035660A (ko) 2022-09-08 2022-09-08 레이저 가공 모니터링 방법 및 장치

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WO2024053800A1 true WO2024053800A1 (fr) 2024-03-14

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004009074A (ja) * 2002-06-04 2004-01-15 Hitachi Via Mechanics Ltd レーザ加工方法およびレーザ加工装置
KR20160075238A (ko) * 2014-12-19 2016-06-29 (주)엔에스 레이저 천공 장치
KR20190135068A (ko) * 2018-05-28 2019-12-06 마이크로 인스펙션 주식회사 레이저 가공장치 및 그 제어방법
WO2021186567A1 (fr) * 2020-03-17 2021-09-23 三菱電機株式会社 Système de traitement au laser
JP2022124799A (ja) * 2021-02-16 2022-08-26 株式会社安川電機 溶接システム、溶接品質の評価方法、及び溶接品の製造方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004009074A (ja) * 2002-06-04 2004-01-15 Hitachi Via Mechanics Ltd レーザ加工方法およびレーザ加工装置
KR20160075238A (ko) * 2014-12-19 2016-06-29 (주)엔에스 레이저 천공 장치
KR20190135068A (ko) * 2018-05-28 2019-12-06 마이크로 인스펙션 주식회사 레이저 가공장치 및 그 제어방법
WO2021186567A1 (fr) * 2020-03-17 2021-09-23 三菱電機株式会社 Système de traitement au laser
JP2022124799A (ja) * 2021-02-16 2022-08-26 株式会社安川電機 溶接システム、溶接品質の評価方法、及び溶接品の製造方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
이용관 등. 인공지능을 이용한 레이저 홀 가공 자동 불량 검출. 한국정밀공학회 2022년도 춘계학술대회논문집. May 2022, pp. 42-43 (LEE, Yongkwan et al. Automatic Failure Detection for the Laser Micro-hole Machining Using Artificial Intelligence. Proceedings of KSPE 2022 Spring Conference.) *

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